Model Comparison

Why the Akaike Information Criterion is as much 'Bayesian' as the Bayesian Information Criterion

According to Rubin (1984), a Bayesianly justifiable analysis is one that “treats known values as observed values of random variables, treats unknown values as unobserved random variables, and calculates the conditional distribution of unknowns given knowns and model specifications using Bayes’ theorem”